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In 2021, the US Food and Drug Administration (FDA), Health Canada, and the UK's Medicine and Healthcare Products Regulatory Agency (MHRA) jointly identified 10 guiding principles that can inform the development of excellent machine learning practices (GMLPs). GMLP supports the development of safe, effective, high quality artificial intelligence/machine learning technologies that can learn from real use and in some cases improve device performance.
In this document, the FDA, Health Canada and MHRA jointly identified five guidelines principles for a given change management plan. These principles are based on the comprehensive GMLP Guide Principles, in particular Principles 10. This states that the deployed model monitors performance and risk retraining is managed.
Advances in digital health technology include artificial intelligence/machine learning-enabled medical devices (MLMD). Regulation expectations consistent with best practices for development and change management as described in the GMLP Guide Principles will help support the quality of such devices. Ultimately, this could lead to patient benefits, such as innovative technology and previous access to more accurate diagnosis.
The change management process helps ensure the continuous safety and effectiveness of the device in the face of changes throughout the device's total product lifecycle (TPLC). However, certain changes to MLMD, such as model or algorithm changes, can be substantial or significant. This allows them to request regulatory oversight, such as additional job reviews. Such regulations expectations do not always coincide with the rapid pace of MLMD development.
Internationally, the medical device community discusses the use of a given change management plan (PCCP) as a way to manage changes to specific devices that normally require pre-marketing regulatory approval. Can be used to use PCCPS.
- Align the regulatory process with a fast and continuous approach to MLMD change management
- Manage risk in a timely and continuous way through monitoring, maintenance, and/or improving device performance.
- Maintain high regulatory standards to ensure the safety and effectiveness of your devices.
In this document, the term PCCP describes the plans proposed by the manufacturer.
- Specific plan changes for devices
- Protocols and control for implementing and controlling these changes
- Evaluation of the impact from revisions.
PCCP may be developed and implemented in a variety of ways in various regulatory jurisdictions.
One of the key objectives of the five guiding principles of PCCPS in MLMD is to provide basic considerations that highlight the properties of robust PCCPs. Another objective of this document is to promote and foster ongoing engagement and collaboration among stakeholders regarding the PCCP concept of MLMD. Similar to the principles of the GMLP Guide, this document is intended to lay the foundations of PCCP and promote international harmony.
International harmony and stakeholder consensus on the core concepts of PCCPS will help support the advances in responsible innovation in the digital health sector.
Continuous feedback is welcome through FDA Public Docket (FDA-2019-N-1185) at Regulations.gov. We look forward to being involved in these efforts. This work is led by the FDA's Digital Health Center of Excellence, Canada Health Canada's Medical Devices Didical Digital Health Division, and MHRA's software and AI teams. Please contact digitalhealth@fda.hhs.gov, software@mhra.gov.uk, and mddpolicypolitiquesdim@hc-sc.gc.ca directly.
Guide principles
1. Focus and boundaries: PCCP describes certain changes that manufacturers are planning to implement. Such changes are limited to changes within the purposes or intended purposes of the original MLMD. This characterization can include:
- Scope of planned changes and MLMD with changed changes
- A plan for safely modifying devices within PCCP boundaries, including methods to validate and validate changes and mechanisms to detect and recover or stop implementations of changes that do not meet the specified performance criteria
- Impact of planned changes
2. Risk-based: The value and reliability of PCCP is enhanced when PCCP intent, design, and implementation is driven by a risk-based approach that adheres to risk management principles. This risk-based perspective is relevant.
- Through TPLC, from the start, implementation and use
- To ensure that individual and cumulative changes are appropriate over time for the device and its environment.
3. Based on evidence: The evidence generated across the device's TPLC is:
- Ensuring the continuous safety and effectiveness of your devices with PCCP
- Demonstrate that benefits outweigh the associated risks
- Ensure that risks are managed and controlled properly
Considerations for evidence supporting PCCP include:
- The methods and metrics used to measure device performance are scientifically and clinically justified in proportion to risk, and are consistent with other evidence collected across TPLC
- It has been specified how to generate evidence demonstrating the benefits and risks of devices before and after changes specified in PCCP
4. Transparent: For PCCPS, best practice is to provide users and other stakeholders with clear, relevant information and detailed plans for continuous transparency. This allows stakeholders to recognize device performance and ensure use before and after changes are implemented. For example, think about it.
- Characterization of data used in development and modification has been demonstrated to reflect the intended population
- Comprehensive testing of planned changes
- Device characterization before and after the implementation of changes
- Monitoring, detection, and response to deviations in device performance
5. Total Product Life Cycle (TPLC) perspective: Creating and using PCCP from a TPLC perspective is:
- Increases PCCP quality and integrity by continuously considering all stakeholder perspectives and risk management practices across the TPLC
- Ensure device safety by using and supporting existing regulatory, quality, and risk management measures across TPLCs, monitoring, reporting and responding to safety concerns
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